Practical Applications In Agriculture Research Articles

Allelopathic potential and competitive traits of sweetpotato cultivars

Allelopathy and competition are components of plant-plant interactions, delimiting the level of interference. Understanding this interaction has practical applications in agriculture. Crop cultivars possessing high allelopathic ability and competitive traits are themselves tools for sustainable weed management, enabling reduced use of herbicides. Greenhouse and field experiments were conducted to assess the weed suppressive ability of selected sweetpotato (Ipomoea batatas L.) cultivars. The effect of nine cultivars on Palmer amaranth (Amaranthus palmeri S. Watson), junglerice (Echinochloa colona L.), and hemp sesbania (Sesbania hederacea P. Mill.) was first evaluated in the greenhouse. The experiment was set up in a completely randomized design with four replications and conducted twice. Sweetpotatoes were cultured in sand. The target weeds were seeded in pots filled with a 2:1 mix of field soil:potting mix and watered with 100-ml aliquot of sweetpotato root leachates once every 2 d. Weed height and shoot biomass were measured. ‘Heartogold’, ‘Centennial’, and ‘Stokes Purple’ were the most allelopathic cultivars. Junglerice was most inhibited by sweetpotato leachates. Nine cultivars were evaluated in the field. Experiments were conducted at Fayetteville and Kibler, Arkansas, USA, in a split-plot design, with weed infestation (broadleaf spp., grass spp., or weed-free) as whole plot and the cultivars as split-plot. Across locations, ‘Beauregard-14’ had the longest vines, whereas ‘Hatteras’ and ‘Heartogold’ had the tallest canopy. ‘Heartogold’ had the largest leaf area. This cultivar reduced weed biomass 2- to 4-fold in both locations. Yield was reduced on average 55 and 68% with grass and broadleaf weeds across locations, respectively. ‘Beauregard-14’ and ‘Bayou Belle-6’were the high-yielding cultivars in Kibler and Fayetteville. The highest yielding cultivars were not the most weed suppressive but did not incur the highest yield loss from weed competition, indicating the ability to withstand weed interference. Cultivar competitiveness, weed-suppressive ability, and weed tolerance are important factors that should be considered before making a cultivar selection.

Emerging Research Topics in the Vibrionaceae and the Squid-Vibrio Symbiosis.

The Vibrionaceae encompasses a cosmopolitan group that is mostly aquatic and possesses tremendous metabolic and genetic diversity. Given the importance of this taxon, it deserves continued and deeper research in a multitude of areas. This review outlines emerging topics of interest within the Vibrionaceae. Moreover, previously understudied research areas are highlighted that merit further exploration, including affiliations with marine plants (seagrasses), microbial predators, intracellular niches, and resistance to heavy metal toxicity. Agarases, phototrophy, phage shock protein response, and microbial experimental evolution are also fields discussed. The squid–Vibrio symbiosis is a stellar model system, which can be a useful guiding light on deeper expeditions and voyages traversing these “seas of interest”. Where appropriate, the squid–Vibrio mutualism is mentioned in how it has or could facilitate the illumination of these various subjects. Additional research is warranted on the topics specified herein, since they have critical relevance for biomedical science, pharmaceuticals, and health care. There are also practical applications in agriculture, zymology, food science, and culinary use. The tractability of microbial experimental evolution is explained. Examples are given of how microbial selection studies can be used to examine the roles of chance, contingency, and determinism (natural selection) in shaping Earth’s natural history.

The Role of Synthetic Microbial Communities (SynCom) in Sustainable Agriculture

Modern agriculture faces several challenges due to climate change, limited resources, and land degradation. Plant-associated soil microbes harbor beneficial plant growth-promoting (PGP) traits that can be used to address some of these challenges. These microbes are often formulated as inoculants for many crops. However, inconsistent productivity can be a problem since the performance of individual inoculants/microbes vary with environmental conditions. Over the past decade, the ability to utilize Next Generation Sequencing (NGS) approaches with soil microbes has led to an explosion of information regarding plant associated microbiomes. Although this type of work has been predominantly sequence-based and often descriptive in nature, increasingly it is moving towards microbiome functionality. The synthetic microbial communities (SynCom) approach is an emerging technique that involves co-culturing multiple taxa under well-defined conditions to mimic the structure and function of a microbiome. The SynCom approach hopes to increase microbial community stability through synergistic interactions between its members. This review will focus on plant-soil-microbiome interactions and how they have the potential to improve crop production. Current approaches in the formulation of synthetic microbial communities will be discussed, and its practical application in agriculture will be considered.

A mechanistic model for nitrogen-limited plant growth.

Nitrogen is often regarded as a limiting factor to plant growth in various ecosystems. Understanding how nitrogen drives plant growth has numerous theoretical and practical applications in agriculture and ecology. In 2004, Göran I. Ågren proposed a mechanistic model of plant growth from a biochemical perspective. However, neglecting respiration and assuming stable and balanced growth made the model unrealistic for plants growing in natural conditions. The aim of the present paper is to extend Ågren's model to overcome these limitations. We improved Ågren's model by incorporating the respiratory process and replacing the stable and balanced growth assumption with a three-parameter power function to describe the relationship between nitrogen concentration (Nc) and biomass. The new model was evaluated based on published data from three studies on corn (Zea mays) growth. Remarkably, the mechanistic growth model derived in this study is mathematically equivalent to the classical Richards model, which is the most widely used empirical growth model. The model agrees well with empirical plant growth data. Our model provides a mechanistic interpretation of how nitrogen drives plant growth. It is very robust in predicting growth curves and the relationship between Nc and relative growth rate.

3D shape sensing and deep learning-based segmentation of strawberries

Automation and robotisation of the agricultural sector are seen as a viable solution to socio-economic challenges faced by this industry. This technology often relies on intelligent perception systems providing information about crops, plants and the entire environment. The challenges faced by traditional 2D vision systems can be addressed by modern 3D vision systems which enable straightforward localisation of objects, size and shape estimation, or handling of occlusions. So far, the use of 3D sensing was mainly limited to indoor or structured environments. In this paper, we evaluate modern sensing technologies including stereo and time-of-flight cameras for 3D perception of shape in agriculture and study their usability for segmenting out soft fruit from background based on their shape. To that end, we propose a novel 3D deep neural network which exploits the organised nature of information originating from the camera-based 3D sensors. We demonstrate the superior performance and efficiency of the proposed architecture compared to the state-of-the-art 3D networks. Through a simulated study, we also show the potential of the 3D sensing paradigm for object segmentation in agriculture and provide insights and analysis of what shape quality is needed and expected for further analysis of crops. The results of this work should encourage researchers and companies to develop more accurate and robust 3D sensing technologies to assure their wider adoption in practical agricultural applications.

Melatonin promotes potassium deficiency tolerance by regulating HAK1 transporter and its upstream transcription factor NAC71 in wheat.

Melatonin (MT) is involved in various physiological processes and stress responses in animals and plants. However, little is known about the molecular mechanisms by which MT regulates potassium deficiency (DK) tolerance in crops. In this study, an appropriate concentration (50μmol/L) was found to enhance the tolerance of wheat plants against DK. RNA-seq analysis showed that a total of 6253 and 5873 differentially expressed genes (DEGs) were separately identified in root and leaf tissues of the DK+MT-treated wheat plants. They functionally involved biological processes of secondary metabolite, signal transduction, and transport or catabolism. Of these, an upregulated high-affinity K transporter 1 (TaHAK1) gene was next characterized. TaHAK1 overexpression markedly enhanced the K absorption, while its transient silencing exhibited the opposite effect, suggesting its important role in MT-mediated DK tolerance. Moreover, yeast one-hybrid (Y1H) was used to screen the upstream regulators of TaHAK1 gene and the transcription factor TaNAC71 was identified. The binding between TaNAC71 and TaHAK1 promoter was evidenced by using Y1H, LUC, and EMSA assays. Transient overexpression of TaNAC71 in wheat protoplasts activated the TaHAK1 expression, whereas its transient silencing inhibited the TaHAK1 expression and aggravated the sensitivity to DK. Exogenous MT application greatly upregulated the expression of TaHAK1 in both transient overexpression and silencing systems. Our findings revealed some molecular mechanisms underlying MT-mediated DK tolerance and helped broaden its practical application in agriculture.

Exogenous RNA as a Regulatory Signal during a Plant's Interaction with the Biotic Environment: An Evolutionary Perspective and Future Applications in Agriculture.

Environmental RNAi (eRNAi) is a sequence-specific regulation of endogenous gene expression in a responsive organism by exogenous RNA. While exogenous RNA transfer between organisms of different kingdoms of life have been unambiguously identified in nature, our understanding of the biological significance of this phenomenon remains obscure, particularly within an evolutionary context. During the last decade multiple reports utilizing various mechanisms of natural eRNAi phenomena have been attempted to develop new agricultural traits and products including weed, disease and insect control. Although these attempts yielded mixed results, this concept remains extremely attractive for many agricultural applications. To better utilize eRNAi for practical applications, we would like to emphasize the necessity of understanding the biological significance of this phenomenon within an evolutionary context and learn from nature by developing advanced tools to identify and study new cases of exogeneous RNA transfer and eRNAi. In this opinion article we would like to look at the exogeneous RNA transfer from an evolutionary perspective, propose that new cases of exogeneous RNA transfer still remain to be identified in nature, and address a knowledge gap in understanding the biological function and significance of RNA transfer. We believe such approach may eventually result in a more successful use of this phenomenon for practical applications in agriculture.

A Slimy Business: the Future of Fish Skin Microbiome Studies.

Fish skin contains a mucosal microbiome for the largest and oldest group of vertebrates, a location ideal for microbial community ecology and practical applications in agriculture and veterinary medicine. These selective microbiomes are dominated by Proteobacteria, with compositions different from the surrounding water. Core taxa are a small percentage of those present and are currently functionally uncharacterized. Methods for skin sampling, DNA extraction and amplification, and sequence data processing are highly varied across the field, and reanalysis of recent studies using a consistent pipeline revealed that some conclusions did change in statistical significance. Further, the 16S gene sequencing approaches lack quantitation of microbes and copy number adjustment. Thus, consistency in the field is a serious limitation in comparing across studies. The most significant area for future study, requiring metagenomic and metabolomics data, is the biochemical pathways and functions within the microbiome community, the interactions between members, and the resulting effects on fish host health being linked to specific nutrients and microbial species. Genes linked to skin colonization, such as those for attachment or mucin degradation, need to be uncovered and explored. Skin immunity factors need to be directly linked to microbiome composition and individual taxa. The basic foundation has been laid, and many exciting future discoveries remain.

Intraspecies variability of the 16S rRNA gene of the soil bacteria Acinetobacter lwoffii and Paenibacillus taichungensis

The functioning of well-studied key groups of soil microorganisms depends on the microbial ecosystem in which they function in interaction with species belonging to other ecological groups. An analysis of the composition of the soil microbiota, and the possibility of analyzing the number of representatives of specific species, remains an urgent task of soil microbiology. Such analysis could be performed using modern and expensive methods such as metagenomics and mass-spectrometry, but some questions could also be answered using real-time PCR. This well-known approach is rather cheap for massive analysis and is ready to present reproducible results for practical agricultural applications. Understanding the variability of the primary structure of 16S rRNA is key to the reliable identification of bacterial species and provides an opportunity to choose the optimal pathways for their detection by PCR. In this work, analysis of the sequences of 16S rRNA of two species of soil bacteria, Acinetobacter lwoffii and Paenibacillus taichungensis is carried out. The most variable and most conservative areas on the level of species are detected. It was proved that conventional variable and conservative areas of the gene have on average nearly the same level of variability on the intraspecies level.

Kinetin/N6-furfuryladenine: A New Neurodegenerative Disease Lead from an Old Plant Cytokine

N6-fufuryladenine (N6FFA), or kinetin, has a long history as a plant cytokine with practical applications in agriculture. This adenosine analog is now commonplace in natural product small molecule chemical screening libraries, and as such has been discovered as active in mammalian disease pathways that include Parkinson’s disease, Huntington’s disease (HD) and Familial Dysautonomia.

Special Issue “Hyperspectral Remote Sensing of Agriculture and Vegetation”

The advent of up-to-date hyperspectral technologies, and their increasing performance both spectrally and spatially, allows for new and exciting studies and practical applications in agriculture (soils and crops) and vegetation mapping and monitoring atregional (satellite platforms) andwithin-field (airplanes, drones and ground-based platforms) scales. Within this context, the special issue has included eleven international research studies using different hyperspectral datasets (from the Visible to the Shortwave Infrared spectral region) for agricultural soil, crop and vegetation modelling, mapping, and monitoring. Different classification methods (Support Vector Machine, Random Forest, Artificial Neural Network, Decision Tree) and crop canopy/leaf biophysical parameters (e.g., chlorophyll content) estimation methods (partial least squares and multiple linear regressions) have been evaluated. Further, drone-based hyperspectral mapping by combining bidirectional reflectance distribution function (BRDF) model for multi-angle remote sensing and object-oriented classification methods are also examined. A review article on the recent advances of hyperspectral imaging technology and applications in agriculture is also included in this issue. The special issue is intended to help researchers and farmers involved in precision agriculture technology and practices to a better comprehension of strengths and limitations of the application of hyperspectral measurements for agriculture and vegetation monitoring. The studies published herein can be used by the agriculture and vegetation research and management communities to improve the characterization and evaluation of biophysical variables and processes, as well as for a more accurate prediction of plant nutrient using existing and forthcoming hyperspectral remote sensing technologies.

Toward agricultural ammonia volatilization monitoring: A flexible polyaniline/Ti3C2Tx hybrid sensitive films based gas sensor

The monitoring of ammonia (NH3) produced in agricultural fields is of great importance due to its huge threat to ecological environment and human health, yet routine monitoring technologies rely on manual completion and complex agricultural environment brings great challenges to the application feasibility of gas sensors. Herein, a flexible chemiresistive gas sensor based on polyaniline (PANI)/Ti3C2Tx hybrid sensitive films is developed toward agricultural NH3 volatilization monitoring. The hybrid film was deposited on the flexible polyimide substrate by an in-situ self-assembly method. The sensor shows high sensitivity, low detection limit, excellent repeatability, high selectivity and good air stability, which could be attributed to the gas-sensing enhancement effects of PANI/Ti3C2Tx Schottky junction and improved protonation degree of PANI in the hybrids. Especially, the sensor exhibits excellent NH3-sensing properties to 20–80 % relative humidity (RH) environments at a temperature range of 10–40 ℃, making it promising for practical agricultural applications. Furthermore, the application feasibility of the sensor to ammonia volatilization monitoring is verified through agricultural simulation experiments. This work provides a fast and accurate gas sensor methodology toward unattended agricultural application, which is an important supplement to the existing technical methods and may greatly pushes forward the development of modernized intelligent agriculture.

Simulation of spatial variability in crop leaf area index and yield using agroecosystem modeling and geophysics‐based quantitative soil information

AbstractAgroecosystem models that simulate crop growth as a function of weather conditions and soil characteristics are among the most promising tools for improving crop yield and achieving more sustainable agricultural production systems. This study aims at using spatially distributed crop growth simulations to investigate how field‐scale patterns in soil properties obtained using geophysical mapping affect the spatial variability of soil water content dynamics and growth of crops at the square kilometer scale. For this, a geophysics‐based soil map was intersected with land use information. Soil hydraulic parameters were calculated using pedotransfer functions. Simulations of soil water content dynamics performed with the agroecosystem model AgroC were compared with soil water content measured at two locations, resulting in RMSE of 0.032 and of 0.056 cm3 cm−3, respectively. The AgroC model was then used to simulate the growth of sugar beet (Beta vulgaris L.), silage maize (Zea mays L.), potato (Solanum tuberosum L.), winter wheat (Triticum aestivum L.), winter barley (Hordeum vulgare L.), and winter rapeseed (Brassica napus L.) in the 1‐ by 1‐km study area. It was found that the simulated leaf area index (LAI) was affected by the magnitude of simulated water stress, which was a function of both the crop type and soil characteristics. Simulated LAI was generally consistent with the observed LAI calculated from normalized difference vegetation index (LAINDVI) obtained from RapidEye satellite data. Finally, maps of simulated agricultural yield were produced for four crops, and it was found that simulated yield matched well with actual harvest data and literature values. Therefore, it was concluded that the information obtained from geophysics‐based soil mapping was valuable for practical agricultural applications.

Gene targeting in livestock

The development of nuclear transfer from tissue culture cells in livestock made it possible in principle to produce animals with subtle, directed genetic changes by in vitro modification of nuclear donor cells. In the short period since nuclear transfer was first performed, gene targeting in livestock has become a reality. Although gene targeting has immediate potential in biotechnology, it is unclear whether there are practical agricultural applications, at present. The first livestock targeting experiments have been directed at engineering animals either to render their organs immunologically compatible for human transplantation, or for improving the commercial production of recombinant proteins in the transgenic mammary gland. All successful examples of targeting have involved target loci that are expressed in the nuclear donor cell line. Two important barriers to the further development of this technology are adapting protocols for non-expressed genes and modifying procedures to enhance the lifespan of targeted cells in vitro. This review provides data that illustrate the difficulty in targeting non-expressed genes and discusses some of the practical issues associated with providing targeted nuclear donor cells that are competent for nuclear transfer.

Two-dimensional knapsack-block packing problem

• We consider a two-dimensional knapsack problem with block packing constraints. • This research is motivated by a practical application in agriculture. • We propose three types of mathematical models for the problem. • Computational experiments show the efficiency of the proposed models. We study the two-dimensional knapsack problem with block packing constraints that is originated from an agricultural company when placing its seed experiments into test fields. The problem extends the classical knapsack problem by considering a block packing requirement. In this problem, a single bin is divided into many disjoint blocks and each block is a union of rectangles. If an item is placed, it should be contained in one of the blocks. The objective is to select a subset of the items to be packed into the bin to maximize the space usage, or equivalently, to minimize the wasted space. We propose three types of mathematical models for addressing the problem. The efficiency of the proposed models is analyzed through numerical studies.

Синтез системы автоматического регулирования температуры жидкости с улучшенными динамическими показателями

An algorithm for synthesizing an automatic liquid temperature control system is proposed. The obtained result can find practical application in agriculture, in processing and preservation of products and in the chemical industry in programmed setting of liquid medium temperature conditions. Dynamic thermal equilibrium is considered in a system consisting of an inductor, a secondary body heated by eddy currents, and a volume of liquid medium. The heat transfer with respect to the environment and the dependence of the inductor and secondary body resistances on temperature are taken into account. The equations describing the heat transfer processes are linearized, and the control system is synthesized subject to the frequency criteria. An algorithm for selecting the parameters of the correcting Butterworth first-order filter is proposed. The synthesis and analysis stages are illustrated by root loci, transient and dynamic characteristics. The problem of taking into account the forcing in the power supply voltage channel in the case of introducing correction devices is considered. The obtained results are supposed to be used in the software of the microcontroller-based automatic control system. The use of the controller will make it possible, in addition to high-quality control of temperature conditions, to optimize the device operation energy efficiency, to identify the parameters of the thermal and electrical models that are not accessible for direct measurement, and to set up the optimal spatial thermal effect on the liquid. In view of a significant inertia of the controlled plant, the above-mentioned set of problems can be solved in the real time mode.

The role of rhizobacteria in rice plants: Growth and mitigation of toxicity

Allelopathic compounds reduce the growth and productivity of upland rice plants, especially in consecutive plantations. The rhizobacteria Pseudomonas fluorescens BRM-32111 and Burkholderia pyrrocinia BRM-32113 have been recorded as growth promoters in rice. This study was developed to understand the effect of the application of rhizobacteria on upland rice plants in consecutive plantations. Experiments were conducted in a completely randomized design with four replications of four treatments: rice seed inoculated with P. fluorescens BRM-32111, rice seed inoculated with B. pyrrocinia BRM-32113 (both sown on soil with rice residue), non-inoculated plants sown on soil with rice residue (control with residue (WR)), and non-inoculated plants on soil with no residue (NR). Roots and seedling growth were adversely affected by allelopathic compounds in control WR plants. Plants inoculated with rhizobacteria P. fluorescens BRM-32111 or B. pyrrocinia BRM-32113 induced an increase of 88% in biomass, 3% in the leaf area, 40% in length, 67% in root biomass, 21% in chlorophyll a, 53% in chlorophyll (a+b), 50% in rate of carbon assimilation (A), 227% in A/rubisco carboxylation efficiency (Ci) and 63% in water use efficiency (WUE) compared to control WR plants. These results indicate that rhizobacteria P. fluorescens BRM-32111 and B. pyrrocinia BRM-32113 increase the tolerance of rice plants to stress from allelochemicals. There are possible practical agricultural applications of these results for mitigating the effects of environmental allelochemistry on upland rice.

Small-scale characterization of vine plant root water uptake via 3-D electrical resistivity tomography and mise-à-la-masse method

Abstract. The investigation of plant roots is inherently difficult and often neglected. Being out of sight, roots are often out of mind. Nevertheless, roots play a key role in the exchange of mass and energy between soil and the atmosphere, in addition to the many practical applications in agriculture. In this paper, we propose a method for roots imaging based on the joint use of two electrical noninvasive methods: electrical resistivity tomography (ERT) and mise-à-la-masse (MALM). The approach is based on the key assumption that the plant root system acts as an electrically conductive body, so that injecting electrical current into the plant stem will ultimately result in the injection of current into the subsoil through the root system, and particularly through the root terminations via hair roots. Evidence from field data, showing that voltage distribution is very different whether current is injected into the tree stem or in the ground, strongly supports this hypothesis. The proposed procedure involves a stepwise inversion of both ERT and MALM data that ultimately leads to the identification of electrical resistivity (ER) distribution and of the current injection root distribution in the three-dimensional soil space. This, in turn, is a proxy to the active (hair) root density in the ground. We tested the proposed procedure on synthetic data and, more importantly, on field data collected in a vineyard, where the estimated depth of the root zone proved to be in agreement with literature on similar crops. The proposed noninvasive approach is a step forward towards a better quantification of root structure and functioning.

Plant thionins: structure, biological functions and potential use in biotechnology

Antimicrobial peptides (AMPs) are important components of defense system in both plants and animals. They represent an ancient mechanism of innate immunity providing rapid first line of defense against pathogens. Plant AMPs are classified into several families: thionins, defensins, nonspecific lipid-transfer proteins, hevein- and knottin-type peptides, hairpinins and macrocyclic peptides (cyclotides). The review focuses on the thionin family. Thionins comprise a plant-specific AMP family that consists of short (~5 kDA) cysteine-rich peptides containing 6 or 8 cysteine residues with antimicrobial and toxic properties. Based on similarity in amino acid sequences and the arrangement of disulphide bonds, five structural classes of thionins are discriminated. The three-dimensional structures of a number of thionins were determined. The amphipathic thionin molecule resembles the Greek letter Г, in which the long arm is formed by two antiparallel α-helices, while the short one, by two parallel β-strands. The residues responsible for the antimicrobial activity of thionins were identified. Thionins are synthesized as precursor proteins consisting of a signal peptide, the mature peptide region and the C-terminal prodomain. Thionins protect plants from pathogenic bacteria and fungi acting directly on the membranes of microorganisms at micromolar concentrations, although their precise mode of action remains unclear. In addition to plant pathogens, thionins inhibit growth of a number of human pathogens and opportunistic microorganisms, such as Candida spp., Saccharomyces cerevisiae, Fusarium solani, Staphylococcus aureus and Escherichia coli. Thionins are toxic to different types of cells including mammalian cancer cell lines. Transgenic plants expressing thionin genes display enhanced resistance to pathogens. A wide range of biological activities makes thionins promising candidates for practical application in agriculture and medicine.

24-Epibrassinolide reduces stress in nematode-infected tomato (Solanum lycopersicum L.) plants cultured in vitro

24-Epibrassinolide (EBL) is considered the most probable brassinosteroid (BR) candidate that could be used for practical application in agriculture. EBL-induced stress-protective properties were evaluated in in vitro-grown tomato (Solanum lycopersicum L.) varieties Pusa Ruby (susceptible to nematodes) and PNR-7 (resistant to nematodes) during nematode pathogenesis. Sterilized tomato seeds treated with 10−11, 10−9, or 10−7 M EBL and germinated in vitro were inoculated with second-stage juveniles of Meloidogyne incognita [(Kofoid and White) Chitwood]. Whole plant analyses of morphological and biochemical parameters 7 d after inoculation showed significant improvements in plant growth and development for both varieties and a highly significant reduction in the number of galls in the susceptible variety. Increased specific activities of antioxidative enzymes (catalase, ascorbate peroxidase, glutathione reductase, glutathione peroxidase, guaiacol peroxidase, and superoxide dismutase) were observed in EBL-treated seedlings of both varieties, but increases were higher in the resistant variety. A highly significant increase in antioxidants (ascorbic acid content, total flavonoid content, total glutathione content, and total phenolic content) was observed in EBL-treated Pusa Ruby seedlings, whereas in PNR-7, significant increases were found except for total flavonoid content, which increased non-significantly. Confocal microscopic images showed amelioration of stress in roots of EBL-treated seedlings as indicated by the decrease in level of green fluorescence in them as compared to untreated and nematode-inoculated roots.